{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "高中体测数据可视化（体测分数_男生，体测分数-女生）\n",
    "\n",
    "1、对男1000米跑、男引体进行等宽分箱操作，分成3份，并使用饼图绘制百分比\n",
    "\n",
    "2、对女800米跑、女跳远进行直方图绘制统计各分数段人数，分成4份\n",
    "\n",
    "3、使用嵌套饼图对比男女生体重指数进行比例统计，分为正常、低体重、超重、肥胖(男女生体重指数参考如下)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1、对男1000米跑、男引体进行等宽分箱操作，分成3份，并使用饼图绘制百分比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.13</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>66</td>\n",
       "      <td>195</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2785</td>\n",
       "      <td>62</td>\n",
       "      <td>170</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>25.120001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
       "      <td>78</td>\n",
       "      <td>225</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
       "      <td>74</td>\n",
       "      <td>7</td>\n",
       "      <td>60</td>\n",
       "      <td>3133</td>\n",
       "      <td>68</td>\n",
       "      <td>174</td>\n",
       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
       "      <td>70</td>\n",
       "      <td>218</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3901</td>\n",
       "      <td>80</td>\n",
       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>3538</td>\n",
       "      <td>74</td>\n",
       "      <td>171</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>18.709999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  男体前屈分数  男引体  \\\n",
       "0   1  男     4.13         72   8.88       66  195     60    12      74    1   \n",
       "1   1  男     4.16         70   7.70       78  225     74    11      74    7   \n",
       "2   1  男     4.09         74   8.45       70  218     70    14      78    1   \n",
       "3   1  男     4.21         68   8.05       74  206     64    13      76    1   \n",
       "4   1  男     3.44         85   7.52       78  210     66    13      76    9   \n",
       "\n",
       "   男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0      0  2785      62  170  72.599998  25.120001  \n",
       "1     60  3133      68  174  52.700001  17.410000  \n",
       "2      0  3901      80  169  46.500000  16.280001  \n",
       "3      0  4946     100  183  79.699997  23.799999  \n",
       "4     68  3538      74  171  54.700001  18.709999  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']  #显示中文\n",
    "boy = pd.read_excel('./体测分数_男生.xls')   #读取文件\n",
    "boy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SJGm26ueRoacleVs7S1Cnx7av63rsdgOPHiswr6NOkiRJ0gzQz6DiOTSLih3SVX4QcGNV3dJjnyuAVybZuqPsAJp1C344nkAlSZIkTbx+Hhm6Jcly4Lgk64HraZKB17YbSZ4LbFlV17S7nQX8JfCFJKcBuwJHAO9zDQJJkiRp5uh3YbLFwPuAdwJPBVYBr6mqi9v6s4Cd2o2qujXJvsDfApcAtwHHAx+dqMAlSZIkbby+EoKquo9mitGe04xW1d49yq4GXrwxwUmSJEmaXP0uTCZJkiRpFjIhkCRJkgaYCYEkSZI0wEwIJEmSpAFmQiBJkiQNMBMCSZIkaYCZEEiSJEkDzIRAkiRJGmAmBJIkSdIAMyGQJEmSBpgJgSRJkjTATAgkSZKkATbmhCDJVkn+Lcm5o7S7Jkl1bbeNO1JJkiRJE27zcexzPDAP+PZIDZJsDiwAjgGu6KhaP47zSZIkSZokY0oIkuwBHAb8cpSm84EtgYur6tpxxiZJkiRpkvX9yFCSLYBPAycAPx+l+SKa3oDV4w9NkiRJ0mQbyxiC97avH+6j7SLgV8A5Se5MsjbJsiTbjDlCSZIkSZOmr0eGkiwAjgb2rqoHkoy2yyJgB+BHwN8BuwN/AzwHeFmP4y8BlgDMnTuXNWvW9Bu/NCX8TGommT9//nSHIEmaRUZNCJJsBpwDLKuq7/d53GOA46pqZfv+m+0MQ/+YZM+quqqzcVUtA5YBDA0NlRc7zTR+JiVJ0mzVTw/B4cAzgP3a2YOGJcnmVfVA9w5VdU2P41zavi4ErupRL0mSJGmK9TOG4LXA04E7aQYKrweeBxwCrE+yU2fjJHOSvKWdkajTY9vXdRsTsCRJkqSJ008PwduA7sHA5wP/RrMmwa2dFVX1YJKlNDMM/VFH1UHAg8A3xh2tJEmSpAk1akJQVY8aTZnkPuD24TECSZ4LbNnxqNApwNlJTgcuAfagSR5Or6qfTlTwkiRJkjbOeFYq7uUsYKd2o6qWJbkfeBfN7EG/AN5PkyhIkiRJmiHGlRBU1e5d7/fu0eY84LzxhSVJkiRpKoxlYTJJkiRJs4wJgSRJkjTATAgkSZKkAWZCIEmSJA0wEwJJkiRpgJkQSJIkSQPMhECSJEkaYCYEkiRJ0gAzIdAm74lPfCJJJm0DJvX4SXjiE584zf8VpcmXZI8kDyTZrqPsCUmqx3bBdMYqSYNkXCsVSzPJnXfeSVVNdxgbZTjxkGarJPOAi4A5XVWL2tf9gDs7ym+firgkSSYEkqRJlGQzYDFwKvBAjyaLgDuq6tIpDUyS9LAxPzKUZKsk/5bk3FHaPS/JN5Lcl+SWJEvjbVBJGjSLgDOAjwNHjVB/7ZRGJEl6hPGMITgemLehBkmeBHwd+C/gVcBHgL8G3jOO80mSNl03A8+uqmOAB3vULwKS5Mr2BtLPkrzbG0iSNHXG9MhQkj2Aw4BfjtL0MCDAQVV1L/D1JE8GjkxyWlX1uihIkmaZqrpjpLr2R/9CYC1wNPABYH/gFOBx7fvufZYASwDmzp3LmjVrJiFqafz8TGommT9/fl/t+k4IkmwBfBo4AXjDKM33Bb7aJgPDLqTpLn4BcHW/55UkzVqbAQcAN1XVTW3ZPyfZhuYG0ilV9evOHapqGbAMYGhoqPq92ElTxc+kNkVj6SF4b/v6YUZPCHYBrugqu6F9nYcJgSZQHbctvP8J0x3GRqnjtp3uEKQp1/YWX9mj6lKaXoCdgdVTGpQkDaC+EoIkC2i6c/euqgf6eLRzO5ou4E73dNR1H98uYI3brsffzerVm/Zvhl133ZXVB/u5V39myx3IJE+jGWd2UVX9oqPqse3ruqmPSpIGz6gJQTtl3DnAsqr6/hiO3Z01PDRSQ7uAtbFmw2dmNvwN0hjNAT4JbEszLemwg4Abq+qWaYlKkgZMPz0EhwPPAPZL0tk+STavql7zSq8FtukqG34m4q6xhylJmm2q6pYky4HjkqwHrqdJBl7bbpKkKdBPQvBa4Ok8cgVJgOcBhyTZuap+0lV3A4+emnReR50kSdAsWvY+4J3AU4FVwGuq6uJpjUqSBkg/CcHbePTd/vOBf6NZk+DWHvtcARyWZOuqGn4G9ACapeh/OM5YJUmbsKo6Fzi3q+w+4Nh2kyRNg1ETgqp61EjHJPcBt1fVyvb9c4Etq+qatslZwF8CX0hyGrArcATwPtcgkCRJkmaOMS1MtgFnATu1G1V1a5J9gb8FLgFuo+lN+OgEnU+SJEnSBBhXQlBVu3e937tHm6uBF48vLEmSJElTYbPpDkCSJEnS9DEhkCRJkgaYCYEkSZI0wEwIJEmSpAFmQiBJkiQNMBMCSZIkaYCZEEiSJEkDzIRAkiRJGmAmBJIkSdIAMyGQJEmSBpgJgSRJkjTA+k4IkhyR5MYk9yT5dpK9R2l/YZLqsT1+o6OWJEmSNCE276dRkncDJwLHAD8E/hS4PMmLq+qHI+y2CDgT+GxX+b3jjFWSJEnSBBs1IUgS4H8Bn6iqD7VlVwAvBd5MkyB07/N4YGfg8qr67oRGLEmSJGnC9NVDAOwP3Db8pqoqyX3ASI//7AYEuHbjwpMkSZI0mUYdQ1CNa6rqljSelORDwC7Ap0bYbRGwHjgiyS+T3Jvk80meMoGxS5IkSdpI/fYQDDsEOLf99zJg5QjtFrXHvg84EHgO8EHgyiTPr6pfdzZOsgRYAjB37lzWrFkzxrA06GbDZ2Y2/A2aGvPnz5/uECRJs0iqqv/GybOBucAQ8AHgkqo6uEe7XYEdq+qbHWUvBr4NvLGqugcaP2xoaKhWrhwpz5AerRnmsmnbfvvtueOOO6Y7DG06Nv0P/QTweqGZJglj+V0lTYG+rhdj6iGoqh8DPwa+keQB4PQk76mqn3W1Ww2s7ir7TpK1wMKxnFMazWR/+foFL0mSZrNRxxAk2TbJIUme3lU1PLtQdzlJ3tC9TkE7W9FjgHXjjFWSJEnSBOtnYbKHaAYP/3lX+StoBg73evD5rcDfJuk8/v7AVsCV44hTkiRJ0iQY9ZGhqronyenAe5Oso+kZ2Ac4Ejixqu5sxxbs2LHmwKnAV4Dzk3yaZlDxicAXq+pbk/GHSJIkSRq7fscQHE2zDsFbgWcC/w68o6qWtfXHAofSDlyoqsuSvKotvwhYS9PLcMzEhS5JkiRpY/WVEFTVA8Ap7dar/k3Am7rKvgx8eePCkyRJkjSZ+hlDIEmSJGmWMiGQJEmSBpgJgSRJkjTATAgkSZKkAWZCIEmSJA0wEwJJkiRpgJkQSJIkSQPMhECSJEkaYCYEkiRJ0gAzIZAkSZIGmAmBJEmSNMD6TgiSHJHkxiT3JPl2kr1Haf/MJF9Ksi7JL5N8JMmWGx2xJEmSpAnTV0KQ5N3AycAy4DXAGuDyJC8Yof2WwNeA3wIOBI4G3gx8dAJiliRJkjRBNh+tQZIA/wv4RFV9qC27AngpzY/8H/bY7Q3AzsA+VfUf7T5bAGck+euqum2C4pckSZK0Efp9ZGh/4MPDb6qqgPuAx4/Qfl/g6uFkoHUhTQKyzzjilCRJkjQJRu0haH/8XwMP9xbsCLwb2AV42wi77QKs6jrOL5L8FzBvYwKWNlbzMZ78fZr/dSRJkma2UROCLocA57b/XgasHKHddsDaHuX3tHWPkGQJsARg7ty5rFmzZoxhSf1bvXr1lJzHz7Emy/z586c7BEnSLDLWhOAqYC9gCPgAsC1w8Ahte91SfahXw6paRpNgMDQ0VF7sJEnSRHriE5/InXfeOennGU+P8lhsv/323HHHHZN6Dg2eMSUEVfVj4MfAN5I8AJye5D1V9bOupmuBbXocYlvgrnFFKkmSNE533nnnrHiUc7ITDg2mUQcVJ9k2ySFJnt5VNTy7UHc5wA10jRVI8mSaJOGG8QQqSZIkaeL1M8vQQ8CngD/vKn8FsJ5mTYJuVwC/m+QZHWUHAA8AK8YRpyRJkqRJ0M8sQ/ckOR14b5J1ND0D+wBHAidW1Z1Jng3sWFXfbXc7H1gKfDHJcTQzE51Cs5aBaxBIkiRJM0S/YwiOBm4D3go8E/h34B3tYGCAY4FDaQcSV9V9SfYFzgQuANYBn26PI0mSJGmG6CshqKoHaO7wnzJC/ZuAN3WV3UCzQJkkSZKkGarflYolSZIkzUImBJKkKZFkjyQPJNmuq/z1SX6U5P4k1yZ5zXTFKEmDyIRAkjTpkswDLgLmdJW/HPgccAmwH/At4IIkvzflQUrSgDIhkCRNmiSbJXkrcDWwVY8mxwCXVdVRVXVlVb0dWEkzk50kaQqYEEiSJtMi4Azg48BRnRVJtgJeQtNz0OlC4OVxSVZJmhImBJKkyXQz8OyqOgZ4sKvuWTSPEN3YVX4D8HjgqZMfniSp33UIJEkas6q6YwPVw4OL13aV39NRf2tnRZIlwBKAuXPnsmbNmokIUwNitnxeZsvfock3f/78vtqZEEiSplv3o0EPjdSwXRBzGcDQ0FD1e7GToP8fRzPdbPk7NHP4yJAkaboM9wxs01W+bft61xTGIkkDy4RAkjRdbqIZVzCvq3wesA74+ZRHJEkDyIRAkjQtqmod8F3gwK6qA4CvVVVNfVSSNHj6SgiSzEnyziSrkqxLcl2St42yz4VJqsf2+IkJXZI0C5wI7JvktCT7JDkTeCFw8jTHJUkDo99BxccB7wY+QLO4zN7AmUm2qqqPjbDPIuBM4LNd5feOI05J0ixUVV9JcijNAmXvoJly9HVV9b3pjUySBseoCUGSLWiSgROqaviOzRVJdqBZSfJRCUHbC7AzcHlVfXcC45UkbaKq6lzg3B7l5wHnTXU8kqRGP48MbUdzl/+SrvI1wFPahKHbbjTTyF27ceFJkiRJmkyjJgRV9auqWlJV/9pVtR+wuqrW99htEbAeOCLJL5Pcm+TzSZ4yATFLkiRJmiDjWpgsyZ8D+wJvGaHJovbY99HMHvEc4IPAlUmeX1W/7jqeK09KUp9clEiSNJEy1lndkhwM/APwhar6kxHa7ArsWFXf7Ch7MfBt4I1V1T3Q+GFDQ0O1cuXKMcUkSQOme2XfgeT1QmORhNkwk+1s+Ts0Zfq6XoxpHYIkRwDnA18G3jhSu6pa3ZkMtGXfoVmVcuFYzilJkiRp8vSdECQ5GTgN+AxwYFX9ZgNt35Bk766yAI+hWX1SkiRJ0gzQ1xiCJO8BjgJOraoj+9jlrcCOSXavqofasv2BrYArxxWpJEmSpAnXzzoEz6AZEPwD4ItJXtTV5Brg6TRjBobXHDgV+ApwfpJP0wwqPhH4YlV9a6KClyRJkrRx+ukheDXNoz57AN/pUb8zcCxwKO3Ahaq6LMmr2vKLaMYOfIpmJUpJkiRJM8SoCUFVnQmcOUqzN7Vb535fphl8LEmSJGmGGtMsQ5IkSZJmFxMCSZIkaYCZEEiSJEkDzIRAkiRJGmAmBJIkSdIAMyGQJEmSBpgJgSRJkjTA+lmYTJIkaZNWx20L73/CdIex0eq4bac7BM1CJgSSJGnWy/F3U1XTHcZGS0K9f7qj0GzjI0OSJEnSADMhkCRJkgZYXwlBkjlJ3plkVZJ1Sa5L8rZR9nlmki+17X+Z5CNJtpyYsCVJkiRNhH7HEBwHvBv4AHA1sDdwZpKtqupj3Y3bH/5fA+4ADgTmAh8GHgv8xcaHLUmSJGkijJoQJNmCJhk4oapObouvSLIDcCTwqIQAeAOwM7BPVf1Hx3HOSPLXVXXbhEQvSZIkaaP088jQdsBngUu6ytcAT2l/6HfbF7h6OBloXUiTgOwznkAlSZIkTbxRewiq6lfAkh5V+wGrq2p9j7pdgFVdx/lFkv8C5o0nUEmSJEkTb1zrECT5c5pegLeM0GQ7YG2P8nvauu7jLaFNOubOncuaNWvGE5YkDYT58+dPdwiSpFlkzAlBkoOBTwKfr6q/31DTHmUP9WpYVcuAZQBDQ0PlxU6SJEmaGmNahyDJEcD5wJeBN26g6Vpgmx7l2wJ3jeWckiRJkiZP3wlBkpOB04DPAAdW1W820PwGusYKJHkyTZJwwzjilCRJkjQJ+l2Y7D3AUcCpVfXmqnpglF2uAH43yTM6yg4AHgBWjCtSSZIkSROun3UIngF8EPgB8MUkL+pqcg3wdGDHqvpuW3YjBAyaAAAT/0lEQVQ+sLRtfxywI3AK8AnXIJAkSZJmjn4GFb8aeAywB/CdHvU7A8cCh9IOJK6q+5LsC5wJXACsAz4NHD0BMUuSJEmaIP2sQ3AmzQ/7DXlTu3XudwPN1KSSJEmSZqgxzTIkSZIkaXYxIZAkSZIGmAmBJEmSNMBMCCRJkqQBZkIgSZIkDTATAkmSJGmAmRBIkiRJA8yEQJIkSRpgJgSSJEnSADMhkCRJkgaYCYEkSZI0wMacECTZI8kDSbYbpd2FSarH9vjxhytJkiRpIm0+lsZJ5gEXAXP6aL4IOBP4bFf5vWM5pyRJkqTJ01dCkGQzYDFwKvBAH+0fD+wMXF5V392oCCVJkiRNmn4fGVoEnAF8HDiqj/a7AQGuHWdckiRJkqZAvwnBzcCzq+oY4ME+2i8C1gNHJPllknuTfD7JU8YbqCRJkqSJ19cjQ1V1xxiPu6g99n3AgcBzgA8CVyZ5flX9urNxkiXAEoC5c+eyZs2aMZ5OkgbH/PnzpzsESdIsMqZBxWNwBvC5qvpm+/6bSVYD3wYOomugcVUtA5YBDA0NlRc7SRocSZ4A3NWj6gtV9cdTHY8kDZpJSQiqajWwuqvsO0nWAgsn45ySpE3WovZ1P+DOjvLbpyEWSRo4k5IQJHkD8J9V9c8dZQEeA6ybjHNKkjZZi4A7qurS6Q5EkgbRZD0y9FZgxyS7V9VDbdn+wFbAlZN0TknSpmkRzkonSdNmzCsV95Lk2Ule1FF0Ks2jQecn+f0khwHnAV+sqm9NxDklSbPGIpqO5CuT3JfkZ0ne3fYsS5Im2UT1EBwLHEqz9gBVdVmSV7XlFwFrgU8Bx0zQ+SRJs0D7o38hzXXiaOADND3KpwCPa993tndWOo3bbPm8zJa/Q5Ov34l6UlWTHMrYDA0N1cqVK6c7DEmayWbNnfMkc4C9gJuq6qaO8rOBPwV26J6qepjXC41FEmbab57xmC1/h6ZMX9eLCXlkSJKk8aiqB6vqys5koHUpsDWw8zSEJUkDxYRAkjRtkjwtyduSPLmr6rHtqzPTSdIkMyGQJE2nOcAngUO6yg8CbqyqW6Y+JEkaLJM17agkSaOqqluSLAeOS7IeuJ4mGXhtu0mSJpkJgSRpui0G3ge8E3gqsAp4TVVdPK1RSdKAMCGQJE2rqrqPZprqY6c7FkkaRI4hkCRJkgaYCYEkSZI0wEwIJEmSpAFmQiBJkiQNMBMCSZIkaYCNOSFIskeSB5JsN0q7Zyb5UpJ1SX6Z5CNJthx/qJIkSeOXZJPftt9+++n+z6hZaEzTjiaZB1xEs7LkhtptCXwNuAM4EJgLfJhmKfq/GFekkiRJ41RVk36OJFNyHmmi9ZUQJNmMZuGYU4EH+tjlDcDOwD5V9R/tMbYAzkjy11V12zjjlSRJkjSB+n1kaBFwBvBx4Kg+2u8LXD2cDLQupElA9hlThJIkSZImTb8Jwc3As6vqGODBPtrvAtzYWVBVvwD+C5g3pgglSZIkTZq+HhmqqjvGeNztgLU9yu9p6x4hyRJgCcDcuXNZs2bNGE8nSYNj/vz50x2CJGkWGdOg4jFKj7KHejWsqmXAMoChoaHyYidJkiRNjclah2AtsE2P8m2BuybpnJIkSZLGaLISghvoGiuQ5Mk0ScINk3ROSZIkSWM0WQnBFcDvJnlGR9kBNFOWrpikc0qSJEkaowlJCJI8O8mLOorOB24BvphkvySHAqcAn3ANAkmSJGnmmKgegmOB7wy/qar7aNYiuBO4gGaV4k8D756g80mSJEmaAGOeZaiqzgXO7Sp7E/CmrrIbaJICSZIkSTPUZI0hkCRJkrQJMCGQJEmSBpgJgSRJkjTATAgkSZKkAWZCIEmSJA0wEwJJkiRpgJkQSJIkSQPMhECSJEkaYCYEkiRJ0gAzIZAkSZIGmAmBJEmSNMD6TgiSvD7Jj5Lcn+TaJK8Zpf01Sapru23jQ5YkSZI0UTbvp1GSlwOfA04FLgdeD1yQ5KVV9e0e7TcHFgDHAFd0VK3f6IglSZIkTZi+EgKaH/aXVdVR7fsrk+wOHAn06imYD2wJXFxV1258mJIkSZImw6iPDCXZCngJcFFX1YXAy5Okx26LaHoDVm90hJIkSZImTT9jCJ4FzAFu7Cq/AXg88NQe+ywCfgWck+TOJGuTLEuyzUZFK0mSJGlC9fPI0Hbt69qu8ns66m/tqlsE7AD8CPg7YHfgb4DnAC/rPkGSJcASgLlz57JmzZp+YpekgTR//vzpDkGSNIv0O4YAoPvRoIc20PYY4LiqWtm+/2Y7w9A/Jtmzqq7qbFxVy4BlAENDQ+XFTpIkSZoa/TwyNNwz0P24z7bt613dO1TVNR3JwLBL29eF/YcnSZIkaTL1kxDcBDwIzOsqnwesA37eWZhkTpK3JNmjq/1j29d14wlUkiRJ0sQbNSGoqnXAd4EDu6oOAL5WVdXV/kFgKfCBrvYH0SQW3xh3tJIkSZImVL9jCE4EvpzkNOBLwB8DLwT2BEjyXGDLqrqmbX8KcHaS04FLgD2A44HTq+qnExi/JEmSpI3QV0JQVV9JcijNYOF30Ew5+rqq+l7b5Cxgp3ajqpYluR94F83sQb8A3k+TKEiSJEmaIfqeZaiqzgPOG6Fu77G0lyRJkjQz9DOoWJIkSdIsZUIgSZIkDTATAkmSJGmAmRBIkiRJA8yEQJIkSRpgJgSSJEnSADMhkCRJkgaYCYEkSZI0wEwIJEmSpAFmQiBJkiQNMBMCSdK0S/L6JD9Kcn+Sa5O8ZrpjkqRB0XdCMNYv6yTPS/KNJPcluSXJ0iTZ+JAlSbNJkpcDnwMuAfYDvgVckOT3pjUwSRoQfSUEY/2yTvIk4OvAfwGvAj4C/DXwngmIWZI0uxwDXFZVR1XVlVX1dmAlcOQ0xyVJA2HzPts9/GXdvr8yye40X9a9egoOAwIcVFX3Al9P8mTgyCSnVdWDGxu4NNl6dWhV1TREIs1eSbYCXgL8RVfVhcAxSVL+jydJk2rUHoKOL+uLuqouBF4+wmNA+wJfbZOBzvY7AC8YZ6zSlOn8WJ977rk9yyVNiGcBc4Abu8pvAB4PPHXKI5KkAdNPD0E/X9a3dtXtAlzRoz3APODqsYUpTY/hG5OHHnqoyYA0ObZrX9d2ld/TUf/wNSbJEmAJwNy5c1mzZs2kB6jBteuuu455n7FeK1avXj3mc0j9mj9/fl/t+kkIxvRl3VG2ofaP4Be8ZqKTTjrpEZ/Fk046iaOPPtrPp6Zdv1/wm5juX1EP9WpUVcuAZQBDQ0M1S/9baIbwaTUNin7HEECfX9bjae8XvGaio48+mve+972PeA+z9seYNF2Gbx5t01W+bft61xTGIkkDqZ9ZhsbzZb12jO2lGSkJn/nMZ3xcSJo8NwEP0jxO2mkesA74+ZRHJEkDpp+EYDxf1jeM0H64TprROruJ3/SmN/Usl7Txqmod8F3gwK6qA4CvOcOQJE2+UROCcX5ZXwG8MsnWXe1vB344zlilKVVVj9okTYoTgX2TnJZknyRnAi8ETp7muCRpIPS7UvEGv6yTPDfJ8zvan9Ue+wtJfj/J4cARwImuQSBJ6lRVXwEOpVnI8jJgL+B1VfW9aQ1MkgZEX4OKq+orSQ6lWaDsHTSP/XR+WZ8F7NRuVNWtSfYF/pZmdePbgOOBj05k8JKk2aGqzgPOm+44JGkQ9T3L0Ia+rKtq7x5lVwMvHndkkiRJkiZdv48MSZIkSZqFTAgkSZKkAWZCIEmSJA0wEwJJkiRpgJkQSJIkSQMsM22xpSS/An463XFIHX6LZupcaaa4rar+YLqDmG5eLzQDeb3QTNPX9WLGJQTSTJNkZVUNTXcckqSZzeuFNlU+MiRJkiQNMBMCSZIkaYCZEEijWzbdAUiSNgleL7RJcgyBJEmSNMDsIZA2AUmekOTiJI+d7lgkSdLsYkKgGSPJPyepPrZPTnesI0ny2CT7dZX9Vhv3c7rK9+2x/9u7/tbr2qpdgT8EfjNpwUuSpIFkQqCZ5pPAgnZ7S1u2oGO7eqQdk+yR5IEk2/Woe32SHyW5P8m1SV7To807ktzUtvl+kj276uckOT7JrUnuTXJlkud2HWZn4PQkn06yxQZifSPwv5M8o0f19cBC4H0dZS8Dfg48LcnTO7a5I51DkjSy8d6ESnLdBtru1NHuJ0nesYHzn5Pk4K6yq5L81UT/rdJoTAg009xeVaurajVwC8Dw+7bs3l47JZkHXATM6VH3cuBzwCXAfsC3gAuS/F5Hm7cAHwM+AewP/Ay4LMmzOg51HPAu4P3Aa4HNga8necJwg6paBbwE2Av46Aixvplm4Nn/qKpbejS5v6qup0kAhr0eeEb736RzW9PrHJKkvoznJtSrutosAF4xlpO2N4wOBB4aV9TSBNt8ugOQuixNsrSzIEn3yPfVHXWbAYuBU4EHRjjmMcBlVXVU+/7KJLsDRwLDPQXHAsuq6kPtcb8B3Aj8T+CvkjyOJhk4vqqWtW2upkkc3kyTTABQVf+Z5EDge0kuB77TEe/pwBuB11TV5X389yDJy4DnAXtV1Te6yv+xn2NIknq6vb3ZRJKnQ3MTargyyaNuQlXVTd1lSe4f43lfATwWuCnJrh3lWwFP6iq7v6p+MsbjS2NiD4FmmrHerVkEnAF8HDiqq44kW9Hcsb+oq+pC4OVpzAN26mxTVb8Bvgz8flv034HHdbW5A/i/HW3oqPsX4I+AK7qqTgVeOEoysDDJj9u2c2h6GgL8364u7G2A/9rAcSRJG7Z0+HsV+Bo0N6E6yvaapPO+E/gC8D1gVcf2AuDorrLu65c04UwItKm7GXh2VR0DPNij/lk0P6pv7Cq/AXg88FRgl7asV5vnJEnb5iHg33u0mTf8Jsm/dF1c1gG/6mh7C3BjxwXnJ13H+xywO3ApcF37+ph23yU0d48+27bdAbizx98sSerPmB8ZSrKwe+wA8Kheg5EkeQGwL3B5VaWqwv+7jgxfZ747XFdVu4/3j5P65SNDmmne3m6dVnW9/+HwP9q79BsyPMB4bVf5PR31G2rzGJof4dsB91ZV92NJ93TsD80jSJ1Tgx4HPBt4Ic2doDuAIzrq13cd7+1tHLcB66rqiCRHt/uur6r7kwwnPk8G/gNJ0lTameZmz1CPug1+JyeZQzOGLDxy/MBr22OuAb4NHJbkSVX1ywmJWBqFCYFmjKrau/N9kj8FDqqqR80INA7pet9rINdobbrrH9Wm8znPJLsBfwy8DrgYOB74P8C2VfX9EeLclSYZuAf4o/bO09vaur9P8vftv88GngncOsJxJEmjG9NNqNbOwE2dYw3G4KM03913DRd0jIW7GPht4MfAvwB/BnxkHOeQxsxHhjQjJDmmRxfsZ4EDRpjabbc+Dz1813+brvJt29e7Rmnzm6q6t23zuPbuTnebu7rKSLIt8E/AZ/h/Xc6raL7cLxxhutFu/0zTZf1P7ftjgN3a7QPt6819HEeS1KWq9u54LCc0P8D/T2dZu3UnDDsBdyTZtce2/Ujna2etO4DmJlFnj/TBNI8MndhRtgx4V3stkSadCYFmik/wyOc2h4D7aKb47Cz/87b9T/s87k00YwvmdZXPo+me/TnN8/mM0GZ4XMENND0Ez+7R5obOgnYg8z+17d/Z1X4pTWLwzT6SmnXtdKvDF47/oElAdgaeAvw3mnEGkqQx2MibUDsDL+WRA3+HtzeMdM6q+nfgWVX1zY44nkkzMcZZVdX5fX4ucDfwj20PgjSp/JBpRqiqh9cfaLthX9pWfbKr/CHglqq6u8/jrgO+SzPfc6cDgK9VYw3N9KEPt2nniN4P+Gpb9C3g/q4227dxfrWj7Cnt++cAr2jP3xnPg8Crgf8P+HaSJe2g5X79kmbGiR+0x7gtySe8YEjSmGzMTaj7gHd29yTQ3GS6bUMnba8Bw54OfJ3m0c9PtVONbgU8iWZCjPfRXGO+0E59LU0axxBoxknyCuBk4ISq+kVX9W48+nnO0ZwIfDnJacCXaJ7rfyGwZ1ebj7ez/nwPOAzYHjgdoKruSfK3wDFJ1tL0CryPZpafv2/jfj5wJfCvwEurqnNhsYdV1b1JXge8l+Z50l155EDjuTS9C7+T5H/TDDJ7CNihqm6kXXytTQKWAS+oKhe3kaQ+VdXtwO3D75P8r/afn+y87iR5MV03oarqf3Qfr320Z2uam0v92gX4CU1vwL90lA9PPQpNQvB3NL0S14/h2NKYmBBoxkjyHJoBtP+TZvrNE5LsTHNH/TqaGXoOYIyDrKrqK0kOpXkG/x00P+ZfV1Xf62jziSRbt+c+jubu+yu7FoNZClRbvy3NTBCv6LhQ/Avwl8DnRvuB3t4lOiHJP9DOSpTkT4BDgP+kGT9wIrCiqm5M8kTgw0k+3HWoX/Po3g9JUp8m6CbU/PZ1LAONr6yq4Wmkz29juQq4oKoeXuwyyXO96aPJlqruRWClqZXk9cApNAO1rgFOrqrPt3WPo/mh/TSaKUC/Bby6qjaZBbnax4h+Duw82mqTSZ7T9gJ0l4fmDtFjuqr+s6oeNahZkrRhPW5CvYVmlp/Om1AXAB+pqjO79h3uof0mcC3wV8D8qvpvHW1+Any4qj7e49w/AY7pSAiGyx+VEEhTwR4CzQRfpfksfqd7Sfh2hp9deu61iaiq/6T3lKW92j4qGWjLi0cviiZJGqMeN6He2HET6hc0Pb2dN6HO6z5GVT2UZB1wVHucnwOPepRI2lTYQyBJkgZGku1oJo141E2o6Zbk8TSLUP56umPRYDEhkCRJkgaYUxVKkiRJA8yEQJIkSRpgJgSSJEnSADMhkCRJkgaYCYEkSZI0wEwIJEmSpAH2/wO+2fpMQqVaTgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 936x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d1 = boy['男1000米跑']\n",
    "d2 = boy['男引体']\n",
    "plt.figure(figsize=(13,6))\n",
    "ax = plt.subplot(121)\n",
    "ax.boxplot([d1], vert = True, labels =['男1000米跑'])\n",
    "ax.set_yticks(np.arange(7,step = 0.5))  #设定Y轴刻度\n",
    "# ax.box(False) # 不显示边框\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.tick_params(labelsize=16)\n",
    "ax.grid(linewidth = 0.5,color = 'k',axis ='y',alpha =0.3)\n",
    "\n",
    "ax = plt.subplot(122)\n",
    "ax.boxplot([d2], vert = True, labels =['男引体'])\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.tick_params(labelsize=16)\n",
    "ax.grid(linewidth = 0.5,color = 'k',axis ='y',alpha =0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,' 男引体评级 ')"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#1000米跑评级\n",
    "plt.figure(figsize=(13,6)) #窗格大小\n",
    "ax = plt.subplot(121)  #子窗口\n",
    "def grading(x):\n",
    "    grade = None\n",
    "    if x > 4.30 or x == 0:\n",
    "        grade = '不及格'\n",
    "    elif x > 3.40:\n",
    "        grade = '及格'\n",
    "    else:\n",
    "        grade = '优秀'\n",
    "    return grade\n",
    "boy['1000米跑评级'] = boy['男1000米跑'].map(grading)  \n",
    "run_grade = boy['1000米跑评级'].value_counts() \n",
    "ax.pie(run_grade,labels=run_grade.index,autopct='%0.2f%%',\n",
    "                            wedgeprops={'width': 0.5},\n",
    "                            pctdistance = 0.75,\n",
    "                            textprops = dict(fontsize = 20))\n",
    "ax.set_title(' 男1000米评级 ',fontsize=32, weight='bold', color='white', backgroundcolor='#c5b783')\n",
    "\n",
    "#引体评级\n",
    "ax = plt.subplot(122)\n",
    "def grading_y(x):\n",
    "    grade = None\n",
    "    if x < 8 :\n",
    "        grade = '不及格'\n",
    "    elif x < 16:\n",
    "        grade = '及格'\n",
    "    else:\n",
    "        grade = '优秀'\n",
    "    return grade\n",
    "boy['男引体评级'] = boy['男引体'].map(grading_y)\n",
    "run_grade = boy['男引体评级'].value_counts() \n",
    "ax.pie(run_grade,labels=run_grade.index,autopct='%0.2f%%',\n",
    "                            wedgeprops={'width': 0.5},\n",
    "                            pctdistance = 0.75,\n",
    "                            textprops = dict(fontsize = 20))\n",
    "ax.set_title(' 男引体评级 ',\n",
    " fontsize=32, weight='bold',\n",
    " color='white', backgroundcolor='#c5b783')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对女800米跑、女跳远进行直方图绘制统计各分数段人数，分成4份"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  女仰卧  \\\n",
       "0   1  女    3.22       100   9.32       72  185     85    16      76   48   \n",
       "1   1  女    4.59        40  11.44       10  148     60     9      66   29   \n",
       "\n",
       "   女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0     85  3775     100  163.0  51.299999  19.309999  \n",
       "1     66  3683     100  163.0  66.599998  25.070000  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "girl = pd.read_excel('./体测分数_女生.xls')   #读取文件\n",
    "girl.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(13,6))\n",
    "ax = plt.subplot(121)  #子窗口\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.grid(linewidth = 0.5,color = 'k',axis ='y',alpha =0.3)\n",
    "ax.set_title(\"女800米跑分数分布\")\n",
    "_ = ax.hist(girl['女800米跑分数'], bins=4, normed=0, facecolor=\"blue\", edgecolor=\"black\", alpha=0.7)\n",
    "\n",
    "\n",
    "ax = plt.subplot(122)  #子窗口\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.set_title(\"女跳远分数分布\")\n",
    "ax.grid(linewidth = 0.5,color = 'k',axis ='y',alpha =0.3)\n",
    "_ = ax.hist(girl['女跳远分数'], bins=4, normed=0, facecolor=\"blue\", edgecolor=\"black\", alpha=0.7)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用嵌套饼图对比男女生体重指数进行比例统计，分为正常、低体重、超重、肥胖(男女生体重指数参考如下)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "plt.pie(p1,\n",
    "autopct=lambda pct: func(pct),\n",
    "radius=1, # 半径\n",
    "pctdistance=0.85, # 百分⽐位置\n",
    "wedgeprops=dict(linewidth=3,width=0.4,edgecolor='w'),  # 饼图格式：间隔线宽、饼图宽度、边界颜⾊\n",
    "labels=labels)\n",
    "\n",
    "\n",
    "# 绘制内部饼图\n",
    "plt.pie(p2,\n",
    "autopct='%0.1f%%',\n",
    "radius=0.7,\n",
    "pctdistance=0.7,\n",
    "wedgeprops=dict(linewidth=3,width=0.7,edgecolor='w'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "      <th>女BMI评级</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "      <td>超重</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "      <td>超重</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "      <td>超重</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>588</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.51</td>\n",
       "      <td>78</td>\n",
       "      <td>9.60</td>\n",
       "      <td>68</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>95</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>2255</td>\n",
       "      <td>70</td>\n",
       "      <td>158.0</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>19.629999</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.00</td>\n",
       "      <td>76</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>36</td>\n",
       "      <td>72</td>\n",
       "      <td>2937</td>\n",
       "      <td>85</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.700001</td>\n",
       "      <td>21.490000</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.45</td>\n",
       "      <td>80</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>15</td>\n",
       "      <td>76</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>2592</td>\n",
       "      <td>76</td>\n",
       "      <td>165.0</td>\n",
       "      <td>48.599998</td>\n",
       "      <td>17.850000</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.01</td>\n",
       "      <td>74</td>\n",
       "      <td>9.67</td>\n",
       "      <td>68</td>\n",
       "      <td>165</td>\n",
       "      <td>70</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>1829</td>\n",
       "      <td>60</td>\n",
       "      <td>154.0</td>\n",
       "      <td>43.599998</td>\n",
       "      <td>18.379999</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.48</td>\n",
       "      <td>50</td>\n",
       "      <td>9.09</td>\n",
       "      <td>74</td>\n",
       "      <td>180</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>2962</td>\n",
       "      <td>85</td>\n",
       "      <td>162.0</td>\n",
       "      <td>55.299999</td>\n",
       "      <td>21.070000</td>\n",
       "      <td>正常</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>586 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  女仰卧  \\\n",
       "0     1  女    3.22       100   9.32       72  185     85    16      76   48   \n",
       "1     1  女    4.59        40  11.44       10  148     60     9      66   29   \n",
       "2     1  女    3.46        80  13.40        0  150     60     7      64   40   \n",
       "3     1  女    3.39        85   9.52       70  172     76    21      90   46   \n",
       "4     1  女    3.43        80   9.79       68  145     50     8      64   34   \n",
       "..   .. ..     ...       ...    ...      ...  ...    ...   ...     ...  ...   \n",
       "588  17  女    3.51        78   9.60       68  150     60    24      95   41   \n",
       "589  17  女    4.00        76  10.18       64  150     60    13      72   36   \n",
       "590  17  女    3.45        80  10.18       64  152     62    15      76   35   \n",
       "591  17  女    4.01        74   9.67       68  165     70    10      68   41   \n",
       "592  17  女    4.48        50   9.09       74  180     80    10      68   46   \n",
       "\n",
       "     女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI 女BMI评级  \n",
       "0       85  3775     100  163.0  51.299999  19.309999     正常  \n",
       "1       66  3683     100  163.0  66.599998  25.070000     超重  \n",
       "2       76  3331     100  157.0  60.000000  24.340000     超重  \n",
       "3       85  3701     100  160.0  50.700001  19.799999     正常  \n",
       "4       70  3592     100  167.0  63.900002  22.910000     超重  \n",
       "..     ...   ...     ...    ...        ...        ...    ...  \n",
       "588     78  2255      70  158.0  49.000000  19.629999     正常  \n",
       "589     72  2937      85  161.0  55.700001  21.490000     正常  \n",
       "590     72  2592      76  165.0  48.599998  17.850000     正常  \n",
       "591     78  1829      60  154.0  43.599998  18.379999     正常  \n",
       "592     85  2962      85  162.0  55.299999  21.070000     正常  \n",
       "\n",
       "[586 rows x 18 columns]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boy = boy[boy['BMI'] != 0.0] #过滤指标为0的同学\n",
    "girl = girl[girl['BMI'] != 0.0]\n",
    "def boy_cond(x):\n",
    "    grade =  None\n",
    "    if x >= 26.4:\n",
    "        grade = '肥胖'\n",
    "    elif x >= 16.5 and x<= 23.2:\n",
    "        grade = '正常'\n",
    "    elif x < 16.5 :\n",
    "        grade = '低体重'\n",
    "    else:\n",
    "        grade = '超重'\n",
    "    return grade\n",
    "\n",
    "def girl_cond(x):\n",
    "    grade =  None\n",
    "    if x >= 25.3:\n",
    "        grade = '肥胖'\n",
    "    elif x >= 16.5 and x<= 22.7:\n",
    "        grade = '正常'\n",
    "    elif x < 16.5 :\n",
    "        grade = '低体重'\n",
    "    else:\n",
    "        grade = '超重'\n",
    "    return grade\n",
    "\n",
    "\n",
    "boy['男BMI评级'] = boy['BMI'].map(boy_cond)\n",
    "girl['女BMI评级'] = girl['BMI'].map(girl_cond)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "正常     438\n",
      "超重      93\n",
      "肥胖      44\n",
      "低体重     11\n",
      "Name: 女BMI评级, dtype: int64\n",
      "正常     352\n",
      "超重      61\n",
      "肥胖      38\n",
      "低体重     15\n",
      "Name: 男BMI评级, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "boy_grade = boy['男BMI评级'].value_counts()\n",
    "girl_grade = girl['女BMI评级'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'体重评级占比')"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# 获取colormap tab20c和tab20b的颜色\n",
    "cmap_c = plt.get_cmap(\"tab20c\")\n",
    "cmap_b = plt.get_cmap(\"tab20b\")\n",
    "\n",
    "# 使用tab20c的全部颜色和tab20b中的 5至8 颜色\n",
    "cmap_1 = cmap_c(np.arange(20))\n",
    "cmap_2 = cmap_b(np.array([4, 5, 6, 7]))\n",
    "\n",
    "# 内圈的颜色是每4个颜色中色彩最深的那个. vstack是将两类颜色叠加在一起\n",
    "inner_colors = np.vstack((cmap_1[::4], cmap_2[0]))\n",
    "# 外圈的颜色是全部24种颜色\n",
    "outer_colors = np.vstack((cmap_1, cmap_2))\n",
    "plt.figure(figsize=(9,9))\n",
    "\n",
    "p1 = plt.pie(boy_grade ,\n",
    "autopct='%0.1f%%' ,\n",
    "radius=1, # 半径\n",
    "pctdistance=0.85, # 百分⽐位置\n",
    "wedgeprops=dict(linewidth=3,width=0.4,edgecolor='w'),  # 饼图格式：间隔线宽、饼图宽度、边界颜⾊\n",
    "colors = outer_colors,\n",
    "labels=boy_grade.index)\n",
    "\n",
    "\n",
    "p2 = plt.pie(girl_grade,\n",
    " autopct='%0.1f%%',\n",
    " radius=0.7,\n",
    " pctdistance=0.7,\n",
    " colors = outer_colors,\n",
    " wedgeprops=dict(linewidth=3,width=0.7,edgecolor='w'))\n",
    "\n",
    "plt.legend(boy_grade.index,loc = 'upper right',bbox_to_anchor = (0.75,0,0.4,1),title =\n",
    "'体重占比\\n男(外环)\\n女(内环)')\n",
    "plt.title('体重评级占比',\n",
    " fontsize=32, weight='bold')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
